How a Life Sciences Company informed their next generation qPCR platform by deeply understanding user workflows, pain points, and unmet needs across academic and biopharma labs worldwide.
A Life Sciences Company set out to inform the next generation of its qPCR platform by deeply understanding users' current workflows, pain points, and unmet needs across academic and biopharma labs worldwide. Key questions included: where bottlenecks occur (hardware, software, analysis), which features most influence system choice, and how data handling (e.g., Wi‑Fi, cloud, remote access) and touchscreen workflows factor into adoption.
PROOF Insights (then PROOF Insights) executed a mixed-methods program:
Up to 30 interviews with qPCR users/decision-makers in the US and EU to map workflows, define "ease of use," and capture desired hardware/software changes. Findings informed quantitative attributes.
A blinded, web-based study across the US, EU, and ANZ/SG targeting users who run qPCR experiments each month and influence purchasing. Deliverables included full analysis, segment cuts, and recommendations. The final achieved dataset comprised N=293 completes, with quotas by region and a balanced mix of academic and biopharma respondents.
Instrument usage, satisfaction, touchscreen use, sample loading, data storage/transfer, analysis software, and feature prioritization were captured; the survey instrument covered role, volume, brands/models, and detailed software and workflow modules.
Academic labs average several qPCR instruments; biopharma averages even more, with more teammates sharing each system—indicating high contention and the need for efficient setup/analysis. The research clarified what components heavily drive primary-system choice.
Many users are unsure whether their systems truly have touchscreens; when present, most who use them employ them for "most/all tasks," but a sizable group still prefers the connected computer for speed/comfort.
All methods were noted and their prevalence tabulated. Among labs with both automated and manual loading, the majority prefer one over the other (redacted).
Run data resides on many systems; biopharma does it differently than academia. Wi‑Fi is widely available in academia; biopharma leverages it more.
Manufacturer software and Excel are the top analysis tools, with Excel favored for transparency/ease. Users want better graphing/visualization and basic statistical testing directly in system software.
The top purchase driver was identified, followed by several others, automation friendliness, and price (with academic labs weighting price higher). Desired "must-haves" include auto software updates and many others (redacted).
Focus on performance and others (redacted).
Clear insights into data handling preferences across academic and biopharma segments.
Understanding of preferred analysis workflows and software integration needs.
Clear differentiation between academic and biopharma user needs and preferences.
This multi-region program gave A Life Sciences Company a clear, evidence-based blueprint for its next-gen qPCR platform: protect core (redacted), modernize (redacted) and remove friction in other areas—while recognizing other important capabilities (redacted). The result is a roadmap aligned to how real teams share systems across devices and environments.
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